China
Africa
Explore chapters and articles related to this topic
Object-Oriented Modeling and Simulation
Published in Derek A. Linkens, CAD for Control Systems, 2020
Sven Erik Mattsson, Mats Andersson, Karl Johan Åström
A recent review of current research activities within continuous-time modeling and simulation is given in the work of Marquardt [29]. He discusses three object-oriented modeling languages: ASCEND [38], MODEL.LA [42], and Omola. He states that though rather different, they build on the same basic ideas from object-oriented programming and from structured knowledge representation. ASCEND is a language and environment for rapid development of equation-based models. It contains many facilities for static simulation. Much effort has been put into designing a user-friendly interface. However, there are no facilities for defining models graphically. MODEL.LA is a modeling language tailored to chemical applications. The modeling tool has knowledge about chemical models and gives guidance and issues warnings. Simulation is not supported. It would be possible to use Omola to define the model classes of MODEL.LA. Object-oriented modeling and simulation are also discussed by Cellier, Zeigler, and Cutler [9].
The assessment of response surface methodology (RSM) and artificial neural network (ANN) modeling in dry flue gas desulfurization at low temperatures
Published in Journal of Environmental Science and Health, Part A, 2023
Robert Makomere, Hilary Rutto, Lawrence Koech
Dry flue gas desulfurization (DFGD) is a pollution control system developed as an alternative to the conventional wet and semi-dry systems. This process can occur in a contactor (reactor), e.g. circulating fluidized bed (CFB), or along the duct (in-duct sorbent injection), depending on the required removal efficiency and operating finances.[9,10] The SOX present in the flue gas is neutralized when in contact with a powdered sorbent, preferably hydrated lime (Ca(OH)2). Sulfur capture capacities and reagent conversion associated with DFGD are lower than those in wet and semi-dry FGD.[11,12] Research methods employed to overcome this has been utilizing additives such as fly ash and bottom ash (zeolitic materials) [13–15] or practising sorbent recirculation.[16,17] Employing optimization procedures through process modeling has become increasingly popular to operate industrial units efficiently. To accomplish this, a variety of simulation techniques are available. The discrete event simulation (DES) is crucial in modeling process environments through time. The change perceived during the process is understood to be happening at a certain moment in time. The ARENA, JaamSim and CloudSim are some of the simulation languages compatible with DES models.[18,19] Process simulation is frequently utilized to forecast industrial processes through the quantitative analysis of phase equilibrium, reaction kinetics, mass and energy balance. Information derived from the algebraic equations is essential in designing and optimizing plant operations. Advanced Simulation Library (ASL), APMonitor, CHEMCAD, Aspen HYSYS, SimSci PRO/II and ASCEND are developer consoles used for process simulation modeling.[20,21] The dynamic simulation models processes approaching a steady state after one or more input conditions have been altered. Energy interactions e.g., momentum and heat, are of interest when computing steady state processes.[22] Computational fluid dynamics is one of the less expensive computation packages employed in the dynamic modeling. This computation languages are however vulnerable to long and extended simulation which inhibit assimilation of this program on small scale experimental analysis.[23]